Jensen Huang thinks building a useful robot takes three computers. Not one supercomputer, not a clever chip, but three distinct machines, each with its own job. The Nvidia CEO says physical AI needs one computer to train the model, one to test it in simulation, and one to run the robot itself. Conveniently, Nvidia sells all three. One brain, three bodies Physical AI is the term for systems that perceive, reason and act in the real world. Think warehouse robots, autonomous machines and factory arms, rather than chatbots answering emails. The training computer comes first. This is where the AI model learns, and Nvidia points to its DGX and Grace systems for the job. The simulation computer sits in the middle. Nvidia’s Omniverse platform handles this layer, building digital twins where robots can practice before touching anything real. The runtime computer lives inside the machine. Nvidia’s example here is Jetson Thor, an edge computer embedded in the robot that makes decisions in real time. Huang shared these views in an October 2026 interview. He leaned hard on digital twins as the key to preparing robots and agents for real-world work. The reasoning is about data. Large language mo...
Nvidia CEO Jensen Huang outlines three-computer architecture for physical AI
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